A platform for crowdsourcing the creation of representative, accurate landcover maps

Environmental Modelling and Software

Volumn 80, Issue , 2016, Pages 41-53

  Estes, L D ^a,b   McRitchie, D ^c   Choi, J ^a   Debats, S ^a   Evans, T ^d   Guthe, W ^a   Luo, D ^a   Ragazzo, G ^a   Zempleni, R ^a   Caylor, K K ^a  

^a Princeton University   (United States)

^b PRINCETON UNIVERSITY   (United States)

^c PRINCETON UNIVERSITY   (United States)

^d INDIANA UNIVERSITY   (United States)

Author keywords

Accuracy assessment; Crowd sourcing; Landcover; Object extraction; Remote sensing; Representative sampling

Indexed keywords

REMOTE SENSING;

ACCURACY ASSESSMENT; CURRENT GENERATION; HIGH RESOLUTION IMAGERY; LAND COVER; OBJECT EXTRACTION; REPRESENTATIVE SAMPLE; REPRESENTATIVE SAMPLING; SUBSTANTIAL ERRORS;

CROWDSOURCING;

ACCURACY ASSESSMENT; DATA SET; GEOMETRY; IMAGE RESOLUTION; LAND COVER; REMOTE SENSING; SAMPLING; SOCIOECONOMIC STATUS;

SOUTH AFRICA;

EID: 84959098456     PISSN: 13648152     EISSN: None     Source Type: Journal    
DOI: 10.1016/j.envsoft.2016.01.011     Document Type: Article

References (49)

1. Ahn L.v., Blum M., Hopper N.J., Langford J. CAPTCHA: using hard AI problems for security. Advances in Cryptology EUROCRYPT 2003. No. 2656 in Lecture Notes in Computer Science 2003, 294-311. Springer, Berlin Heidelberg. E. Biham (Ed.).
2. Allahbakhsh M., Benatallah B. Quality control in crowdsourcing systems. IEEE Internet Comput. 2013, 17(2):76-81.
3. Allouche O., Tsoar A., Kadmon R. Assessing the accuracy of species distribution models: prevalence, kappa and the true skill statistic (TSS). J. Appl. Ecol. Dec. 2006, 43(6):1223-1232.
4. Biederman I. Recognition-by-components: a theory of human image understanding. Psychol. Rev. 1987, 94(2):115.
5. Bivand R., Rundel C. Rgeos: Interface to Geometry Engine-open Source (GEOS). R Package Ver. 0.33 2013, http://cran.r-project.org/web/packages/rgeos/index.html.
6. Conway J., Eddelbuettel D., Nishiyama T., Prayaga S.K., Tiffin N. RPostgreSQL: R Interface to the PostgreSQL Database System (2010) 2012, R package version 0.1-7.
7. Debats S., Luo D., Estes L., Fuchs T., Caylor K. A generalized computer vision approach to mapping agricultural fields in Sub-Saharan Africa. PeerJ Prepr. 2015, 3:e1688.
8. Developers G. Google Maps 2012, API.
9. Estes L.D., Beukes H., Bradley B.A., Debats S.R., Oppenheimer M., Ruane A.C., Schulze R., Tadross M. Projected climate impacts to South African maize and wheat production in 2055: a comparison of empirical and mechanistic modeling approaches. Glob. Change Biol. 2013, 19(12):3762-3774.
10. Estes L.D., Bradley B.A., Beukes H., Hole D.G., Lau M., Oppenheimer M.G., Schulze R., Tadross M.A., Turner W.R. Comparing mechanistic and empirical model projections of crop suitability and productivity: implications for ecological forecasting. Glob. Ecol. Biogeogr. 2013, 22(8):1007-1018.
11. Estes L.D., Paroz L.-L., Bradley B.A., Green J.M., Hole D.G., Holness S., Ziv G., Oppenheimer M.G., Wilcove D.S. Using changes in agricultural utility to quantify future climate-induced risk to conservation. Conserv. Biol. Apr. 2014, 28(2):427-437.
12. Flanagin A.J., Metzger M.J. The credibility of volunteered geographic information. GeoJournal Jul. 2008, 72(3-4):137-148.
13. Fraternali P., Castelletti A., Soncini-Sessa R., Ruiz C.V., Rizzoli A.E. Putting humans in the loop: social computing for water resources management. Environ. Model. Softw. 2012, 37:68-77.
14. Fritz S., McCallum I., Schill C., Perger C., Grillmayer R., Achard F., Kraxner F., Obersteiner M. Geo-Wiki.Org: the use of crowdsourcing to improve global land cover. Remote Sens. Aug. 2009, 1(3):345-354.
15. Fritz S., McCallum I., Schill C., Perger C., See L., Schepaschenko D., van der Velde M., Kraxner F., Obersteiner M. Geo-Wiki: an online platform for improving global land cover. Environ. Model. Softw. May 2012, 31:110-123.
16. Fritz S., See L. Identifying and quantifying uncertainty and spatial disagreement in the comparison of global land cover for different applications. Glob. Change Biol. 2008, 14(5):1057-1075.
17. Fritz S., See L., McCallum I., You L., Bun A., Moltchanova E., Duerauer M., Albrecht F., Schill C., Perger C., Havlik P., Mosnier A., Thornton P., Wood-Sichra U., Herrero M., Becker-Reshef I., Justice C., Hansen M., Gong P., Abdel Aziz S., Cipriani A., Cumani R., Cecchi G., Conchedda G., Ferreira S., Gomez A., Haffani M., Kayitakire F., Malanding J., Mueller R., Newby T., Nonguierma A., Olusegun A., Ortner S., Rajak D.R., Rocha J., Schepaschenko D., Schepaschenko M., Terekhov A., Tiangwa A., Vancutsem C., Vintrou E., Wenbin W., van der Velde M., Dunwoody A., Kraxner F., Obersteiner M. Mapping global cropland and field size. Glob. Change Biol. 2015, 21(5):1980-1992.
18. Fritz S., See L., Rembold F. Comparison of global and regional land cover maps with statistical information for the agricultural domain in Africa. Int. J. Remote Sens. 2010, 31(9):2237-2256.
19. Fritz S., You L., Bun A., See L., McCallum I., Schill C., Perger C., Liu J., Hansen M., Obersteiner M. Cropland for sub-Saharan Africa: a synergistic approach using five land cover data sets. Geophys. Res. Lett. 2011, 38:L04404.
20. Frhlich B., Bach E., Walde I., Hese S., Schmullius C., Denzler J. Land cover classification of satellite images using contextual information. ISPRS Annals of the Photogrammetry. Remote Sens. Spatial Inf. Sci. 2013, 3:W1.
21. GeoTerraImage South African Crop Field Boundaries. Technical Report 2008, http://www.geoterraimage.com.
22. Gibbs H.K., Ruesch A.S., Achard F., Clayton M.K., Holmgren P., Ramankutty N., Foley J.A. Tropical forests were the primary sources of new agricultural land in the 1980s and 1990s. Proc. Natl. Acad. Sci. Sep. 2010, 107(38):16732-16737.
23. Gross D., Dubois G., Pekel J.-F., Mayaux P., Holmgren M., Prins H., Rondinini C., Boitani L. Monitoring land cover changes in African protected areas in the 21st century. Ecol. Inf. Mar. 2013, 14:31-37.
24. Hansen M.C., Potapov P.V., Moore R., Hancher M., Turubanova S.A., Tyukavina A., Thau D., Stehman S.V., Goetz S.J., Loveland T.R., Kommareddy A., Egorov A., Chini L., Justice C.O., Townshend J.R.G. High-resolution global maps of 21st-Century Forest cover change. Science Nov. 2013, 342(6160):850-853.
25. Hardy M., Dziba L., Kilian W., Tolmay J. Rainfed farming systems in South Africa. Rainfed Farming Systems 2011, 395-432. Springer, Netherlands. P. Tow, I. Cooper, I. Partridge, C. Birch (Eds.).
26. Howe J. The rise of crowdsourcing. Wired Mag. 2006, 14(6):1-4.
27. Jacobson A., Dhanota J., Godfrey J., Jacobson H., Rossman Z., Stanish A., Walker H., Riggio J. A novel approach to mapping land conversion using google Earth with an application to East Africa. Environ. Model. Softw. Oct. 2015, 72:1-9.
28. Jain M., Mondal P., DeFries R.S., Small C., Galford G.L. Mapping cropping intensity of smallholder farms: a comparison of methods using multiple sensors. Remote Sens. Environ. Jul. 2013, 134:210-223.
29. Laurance W.F., Camargo J.L., Luizo R.C., Laurance S.G., Pimm S.L., Bruna E.M., Stouffer P.C., Bruce Williamson G., Bentez-Malvido J., Vasconcelos H.L., Van Houtan K.S., Zartman C.E., Boyle S.A., Didham R.K., Andrade A., Lovejoy T.E. The fate of Amazonian forest fragments: a 32-year investigation. Biol. Conserv. Jan. 2011, 144(1):56-67.
30. Liang X., Lettenmaier D.P., Wood E.F., Burges S.J. A simple hydrologically based model of land surface water and energy fluxes for general circulation models. J. Geophys. Res. 1994, 99(D7):14415.
31. Licker R., Johnston M., Foley J.A., Barford C., Kucharik C.J., Monfreda C., Ramankutty N. Mind the gap: how do climate and agricultural management explain the yield gap of croplands around the world?. Glob. Ecol. Biogeogr. Nov. 2010, 19(6):769-782.
32. Lintott C.J., Schawinski K., Slosar A., Land K., Bamford S., Thomas D., Raddick M.J., Nichol R.C., Szalay A., Andreescu D., Murray P., Vandenberg J. Galaxy zoo: morphologies derived from visual inspection of galaxies from the Sloan digital sky survey. Mon. Not. R. Astron. Soc. Sep. 2008, 389(3):1179-1189.
33. Lobell D.B. The use of satellite data for crop yield gap analysis. Field Crop. Res. Mar. 2013, 143:56-64.
34. Marvit M.Z. How Crowdworkers Became the Ghosts in the Digital Machine. The Nation Feb. 2014.
35. Monfreda C., Ramankutty N., Foley J.A. Farming the planet: 2. Geographic distribution of crop areas, yields, physiological types, and net primary production in the year 2000. Glob. Biogeochem. Cycles 2008, 22:GB1022.
36. Ohori K.A., Ledoux H., Meijers M. Validation and automatic repair of planar partitions using a constrained triangulation. Photogramm. - Fernerkund. - Geoinfo. Oct. 2012, 2012(5):613-630.
37. Ozdarici-Ok A., Akyurek Z. Object-based classification of multi-temporal images for agricultural crop mapping in Karacabey Plain, Turkey. ISPRS - International Archives of the Photogrammetry Sep. 2014, 127-132. Remote Sensing and Spatial Information Sciences, XL-7.
38. Ozdarici-Ok A., Ok A.O., Schindler K. Mapping of agricultural crops from single high-resolution multispectral ImagesData-driven smoothing vs. Parcel-Based smoothing. Remote Sens. May 2015, 7(5):5611-5638.
39. Ramankutty N., Evan A.T., Monfreda C., Foley J.A. Farming the planet: 1. Geographic distribution of global agricultural lands in the year 2000. Glob. Biogeochem. Cycles Jan. 2008, 22:19.
40. Ruesch A., Gibbs H.K. New IPCC Tier-1 Global Biomass Carbon Map for the Year 2000. Carbon Dioxide Information Analysis Center (CDIAC) 2008, Oak Ridge National Laboratory, Oak Ridge, Tennessee, Available online at:. http://cdiac.ornl.gov/epubs/ndp/global_carbon/carbon_documentation.html.
41. Rulli M.C., Saviori A., D'Odorico P. Global land and water grabbing. Proc. Natl. Acad. Sci. Jan. 2013, 110(3):892-897.
42. Schellekens J., Brolsma R., Dahm R., Donchyts G., Winsemius H. Rapid setup of hydrological and hydraulic models using open street map and the SRTM derived digital elevation model. Environ. Model. Softw. Nov. 2014, 61:98-105.
43. Schroff F., Criminisi A., Zisserman A. Object Class Segmentation Using Random Forests 2008, 54.1-54.10. British Machine Vision Association.
44. Searchinger T.D., Estes L., Thornton P.K., Beringer T., Notenbaert A., Rubenstein D., Heimlich R., Licker R., Herrero M. High carbon and biodiversity costs from converting Africa's wet savannahs to cropland. Nat. Clim. Change May 2015, 5(5):481-486.
45. See L., Fritz S., You L., Ramankutty N., Herrero M., Justice C., Becker-Reshef I., Thornton P., Erb K., Gong P., Tang H., van der Velde M., Ericksen P., McCallum I., Kraxner F., Obersteiner M. Improved global cropland data as an essential ingredient for food security. Glob. Food Secur. Mar. 2015, 4:37-45.
46. Services A.W. Amazon Mechanical Turk 2012.
47. Sullivan B.L., Wood C.L., Iliff M.J., Bonney R.E., Fink D., Kelling S. eBird: a citizen-based bird observation network in the biological sciences. Biol. Conserv. Oct. 2009, 142(10):2282-2292.
48. Tokarczyk P., Wegner J., Walk S., Schindler K. Features, color spaces, and boosting: new insights on semantic classification of remote sensing images. IEEE Trans. Geosci. Remote Sens. Jan. 2015, 53(1):280-295.
49. Yan L., Roy D.P. Automated crop field extraction from multi-temporal web enabled landsat data. Remote Sens. Environ. Mar. 2014, 144:42-64.